Predicting Chroma from Luma with Frequency Domain Intra Prediction

TL;DR

This paper introduces a frequency domain intra prediction method for chroma based on luma, suitable for codecs with lapped transforms, demonstrating lower complexity and improved prediction accuracy in experiments.

Contribution

The paper proposes a novel frequency domain chroma prediction technique that works with lapped transforms, enhancing prediction efficiency and accuracy over previous spatial models.

Findings

Frequency domain predictor outperforms spatial models in accuracy.

Lower complexity algorithm achieves better chroma prediction.

Experimental results validate the effectiveness within the Daala codec.

Abstract

This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level. Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V). In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries and thus neighboring blocks are unavailable during intra-prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low-complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.